Adebamowo et al. BMC Medical Genetics(2020) 21:231
https://doi.org/10.1186/s12881-020-01156-1

RESEARCH ARTICLE

Open Access

Genome-wide association study ofprevalent and persistent cervical high-risk
human papillomavirus (HPV) infection
Sally N. Adebamowo1,2* , Adebowale A. Adeyemo3, Charles N. Rotimi3, Olayinka Olaniyan4, Richard Offiong5,
Clement A. Adebamowo1,2,6,7 and for the H3Africa ACCME Research Group

Abstract
Background: Genetic factors may influence the susceptibility to high-risk (hr) human papillomavirus (HPV) infection
and persistence. We conducted the first genome-wide association study (GWAS) to identify variants associated withcervical hrHPV infection and persistence.
Methods: Participants were 517 Nigerian women evaluated at baseline and 6 months follow-up visits for HPV. HPV
was characterized using SPF10/LiPA25. hrHPV infection was positive if at least one carcinogenic HPV genotype was
detected in a sample provided at the baseline visit and persistent if at least one carcinogenic HPV genotype was
detected in each of the samples provided at the baseline and follow-up visits. Genotyping was done using theIllumina Multi-Ethnic Genotyping Array (MEGA) and imputation was done using the African Genome Resources
Haplotype Reference Panel. Association analysis was done for hrHPV infection (125 cases/392 controls) and for
persistent hrHPV infection (51 cases/355 controls) under additive genetic models adjusted for age, HIV status andthe first principal component (PC) of the genotypes.
Results: The mean (±SD) age of the study participants was 38 (±8) years, 48% were HIV negative, 24% were hrHPV
positive and 10% had persistent hrHPV infections. No single variant reached genome-wide significance (p < 5 X
10− 8). The top three variants associated with hrHPV infections were intronic variants clustered in KLF12 (all OR: 7.06,
p = 1.43 × 10− 6). The top variants associated with cervical hrHPV persistence were in DAP (OR: 6.86, p = 7.15 × 10− 8),
NR5A2 (OR: 3.65, p = 2.03 × 10− 7) and MIR365–2 (OR: 7.71, p = 2.63 × 10− 7) gene regions.
Conclusions: This exploratory GWAS yielded suggestive candidate risk loci for cervical hrHPV infection andpersistence. The identified loci have biological annotation and functional data supporting their role in hrHPV
infection and persistence. Given our limited sample size, larger discovery and replication studies are warranted tofurther characterize the reported associations.

* Correspondence: sadebamowo@som.umaryland.edu
1
Department of Epidemiology and Public Health, University of Maryland
School of Medicine, 660 West Redwood Street, Howard Hall, Room 119,
Baltimore, MD 21201, USA
2
University of Maryland Greenebaum Comprehensive Cancer Center,
University of Maryland School of Medicine, Baltimore, MD, USA
Full list of author information is available at the end of the article© The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,
which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give
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permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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Adebamowo et al. BMC Medical Genetics(2020) 21:231

Background
Human papillomavirus (HPV) is a highly conserved
double-stranded DNA virus that has coevolved withhuman populations for millennia [1]. Over 150 types of
HPV have been identified and about 40 types primarily
infect stratified cutaneous or mucosal epithelia [2]. HPV
infections are among the most common sexually transmitted infections globally [3]. While most infections arecleared naturally by the host’s immune system in ~ 2
years, the infection persists in about 10% of thoseaffected [4]. Persistent infection by high-risk (hr) HPV is
a risk factor for many epithelial cancers including headand neck, anal and cervical cancers. Susceptibility to cervical hrHPV infection, its persistence and progression toneoplastic disease are determined by epidemiologic andgenetic factors. Many epidemiologic risk factors for cervical hrHPV infection including oral contraceptives,
cigarette smoking, multiple sexual partners and coinfection with HIV are well documented [5–8], however
little is known about the genetic risk factors.
Wang et. al evaluated a panel of 7140 candidate single
nucleotide polymorphisms (SNP) in 305 candidate
genes/regions selected based on a priori hypothesesof their association with HPV infection and cervical cancer, within the population-based Guanacaste cohort in
Costa Rica. They reported that SNPs in Deoxyuridine
Triphosphatase (DUT), General Transcription Factor
IIH Subunit 4 (GTF2H4), 2′-5′-Oligoadenylate Synthetase 3 (OAS3) and Sulfatase 1 (SULF1) gene regions wereassociated with HPV persistence, while SNPs in theTransmembrane Channel Like (TMC) 6 and TMC8 generegions were associated with progression to cervicalintraepithelial neoplasia (CIN) 3 and cervical cancer [9].
In a subsequent study in the same cohort, the investigators examined 18,310 SNPs in 1113 genes and reported
that SNPs in PRDX3 and RPS19 were associated with
HPV persistence and progression from persistent HPV
infection to CIN3+ [10]. We examined the association
between the aforementioned SNPs and prevalent hrHPV
infection in African women, and successfully replicated
RPS19:rs2305809 and TYMS:rs2342700 [11].
While the previous candidate gene studies have provided insight into the genetic risk of HPV infection andpersistence, agnostic approaches such as genome-wide
association studies (GWAS), which interrogate the entire
genome would be more useful to uncover novel susceptibility loci for cervical hrHPV infections. A GWAS of
cervical hrHPV infection, can also identify novel biomarkers and potential therapeutic targets in cervicalcancer, however, none have been conducted to date. We
therefore conducted this GWAS of cervical hrHPV
infections and tested previously reported associations
between genes/regions and prevalent and persistentcervical hrHPV infections.

Page 2 of 10

Methods
Study population

We studied 544 women participating in a cohort
study of cervical HPV infection and cervical cancer at
National Hospital, Abuja and University of Abuja
Teaching Hospital, Nigeria, and enrolled between
2012 and 2014, as previously described [5, 12–14]. All
the study participants were 18 years of age or older,
had a history of vaginal sexual intercourse, were notcurrently pregnant and had no history of hysterectomy. We collected data on socio-demographic characteristics, sexual and reproductive history, andconfirmed participants’ HIV status from hospital medical records at study entry. Participants were asked toreturn for follow-up visits after 6 months, at whichtime, the history, physical examinations and sample
collections were repeated. We collected venous blood
samples and performed pelvic examinations on all
the study participants at each study visit. Elution
swab system (Copan, Italy) was used to collect exfoliated cervical cells, which were inserted in 1 ml Amies’
transport media (Copan).
HPV detection by SPF10/LiPA25

We extracted DNA from the cervical exfoliated cells as
previously described [11]. Samples were tested for HPV
DNA by hybridization of SPF10 amplimers to a mixtureof general HPV probes recognizing a broad range ofhigh-risk, low-risk, and possible hrHPV genotypes in a
microtiter plate format, as described previously [15]. All
samples determined to be HPV DNA positive by SPF10DNA Enzyme Immunoassay (DEIA) were genotyped
using the LiPA25 version 1. The LiPA25 assay provides
type-specific information for 25 different HPV genotypes
simultaneously and identifies infection by one or moreof 13 hrHPV genotypes: 16, 18, 31, 33, 35, 39, 45, 51, 52,
56, 58, 59, and 68 [16, 17]. However, as this assay does
not differentiate between HPV 68 and 73, we defined
this HPV genotype (i.e. HPV68/73) as low-risk. We
defined hrHPV infection as prevalent if at least one
hrHPV genotype was detected in the baseline sample
and persistent if at least one hrHPV genotype was
detected in samples provided at both the baseline andfollow-up visits. We defined persistently negative as
absence of hrHPV genotype in the baseline and followup visit samples.
Genotyping and imputation

Samples from the study participants were genotyped
using the Illumina Multi-Ethnic Global Array (MEGA)
which has ~ 1.7 million markers. Sample-level genotype
call rate was at least 0.95 for all the study participants.
We filtered out from the genotyped dataset SNPs that
did not meet the following criteria: autosomal SNPs

Adebamowo et al. BMC Medical Genetics(2020) 21:231(n = 78,713), variant missingness < 0.05 (n = 96,410),
Hardy-Weinberg equilibrium (HWE) p > 1 × 10–6 (n =7692) and minor allele frequency (MAF) > = 0.01 (n =564,791). The resulting 958,363 SNPs that passed thesequality control filters had a SNP success rate of 0.9985
and were used as the basis for imputation.
Imputation was performed using the Sanger Imputation
Service (https://imputation.sanger.ac.uk/) [18]. Prephasing was done with the Eagle2 algorithm [19] and imputation was done with positional Burrows-Wheelertransform (PBWT) [20]. The reference panel used was theAfrican Genome Resources Haplotype Reference Panel, an
African genome imputation reference panel based on
9912 haplotypes (4956 samples) which includes all Africanand non-African 1000 Genomes Phase 3 populations andadditional African genomes from Uganda, Ethiopia, Egypt,
Namibia and South Africa (including 2298 African samples with whole genome sequence data from the African
Genome Variation Project (AGVP) [21] and the Uganda
2000 Genomes Project (UG2G) [22]. The IMPUTE2INFO score was used as a quality metric to evaluate theuncertainty in genotype imputation. Imputation yielded a
total number of ~ 104 million markers. We filtered theresulting imputation dataset for variants with info score ≥0.3 and MAF ≥ 0.01, with a final set of ~ 18 million SNPs
which was used for association analysis.
Statistical analysis

From the original set of 544 women, we excluded 27
women from the baseline analyses because of incomplete data (5 missing HPV, 22 missing both HPV
and HIV results), leaving only 517 women in thebaseline analyses. Of the 517 women, we excluded
those who did not return for the follow-up visit (n =9), those with missing HPV results (n = 35) and included the remaining 473 women in the analyses for
persistent hrHPV infections. For the prevalent
hrHPV analysis, we compared 125 women with cervical hrHPV infections (cases) to 392 women without
cervical hrHPV infections at baseline (controls). For
the persistent hrHPV analysis, we compared 51
women with hrHPV infection at both the baseline
and follow-up visits (cases) to 355 women without
hrHPV infections at either the baseline or follow-up
visits (controls). Using LD-pruned SNP genotype
data available on the same women, we computed
principal components based on the variancestandardized relationship matrix with PLINK 1.9 [23,24] using the parameters “--indep 50 5 2” , namely
with a window size of 50 SNPs, 5 SNPs to shift thewindow at each step and a variance inflation factorof 2. We found that the first principal component
was significant in the test for population differentiation and included it in downstream association

Page 3 of 10

analyses. The association between the genetic variants and prevalent or persistent hrHPV infection was
estimated using unconditional multivariate logistic
regression, assuming an additive genetic model adjusted for age, HIV status and the first principal
component. Genome-wide significance was set at pvalue < 5 × 10− 8. We used an additive genetic model
adjusted for HIV status to test for replication of SNPs
associated with HPV and cervical neoplasia in otherpopulations and considered p-values < 0.05 as statistically significant evidence for replication. The analyses
were conducted using PLINK.

Results
The mean (±SD) age of the participants was 38 (±8)
years while their mean (±SD) body mass index (BMI
[kg/m2]) was 27 (±6). About half of the participants
were HIV positive (52%, 270/517), 24% (125/517)
had prevalent cervical hrHPV infections at baseline
and 11% (51/473) had persistent hrHPV infections.
The distribution of type-specific prevalent and persistent cervical hrHPV infections is shown in Table 1.
Non HPV16/18 were more prevalent in the study
population. The prevalence of HPV16 and HPV18 in
the study population were 2% (10/517) and 4% (8/517), respectively. About 8% (10/125) of the womenwith cervical hrHPV infections had HPV16 and 16%(20/125) had HPV18 at baseline. HPV52 and HPV35
were the most prevalent HPV genotypes in the study
population. About 7% (37/517) of the study population had HPV52, which accounted for about a thirdof the HPV positive infections at baseline. HPV52
and HPV35 were also more likely to persist, compared to the other hrHPV types. About 19% of theparticipants had single cervical hrHPV infections
and ~ 9% of the participants had multiple cervical
hrHPV infections at both visits. Participants returned
for follow-up visits at a median (IQR) time of 5.7(5.4–7.5) months.
The Manhattan plot, Fig. 1, shows all the SNPs andTable 2 shows the top 20 SNPs associated with prevalentcervical hrHPV infections. A cluster of SNPs (D’ = 1,
r2 = 1) located on chromosome 13, rs149473200,
rs147344426 and rs151071053 (Odds Ratio [OR], p-value
for all SNPs was OR: 7.06, p = 1.43 × 10− 6), had thestrongest association with cervical prevalent hrHPV. The
regional plot for rs149473200 in Fig. 1 shows that thecluster of SNPs are intronic in Krüppel-like Factor 12
gene (KLF12) and shows the surrounding markers. SNPs
near Long Intergenic Non-Protein Coding RNA 290
gene (NCRNA00290) also had a borderline genome-wide
significant association with prevalent hrHPV.
The SNP with the strongest association was located on
Chr5:10847898, OR: 6.86, p = 7.15 × 10− 8, Table 3. This(2020) 21:231

Adebamowo et al. BMC Medical Genetics

Page 4 of 10

Table 1 Distribution of Type-Specific Prevalent and Persistent Cervical High-Risk (hr) HPV Infections by HIV status
HPV Type

Prevalent Infections

Persistent Infections

Total
n = 517

HIV Negativen = 247

HIV Positiven = 270

Total
n = 473

HIV Negativen = 223

HIV Positiven = 250hrHPV Positive

125 (24.2%)

37 (14.9%)

88 (32.6%)

51 (10.8%)

10 (0.0%)41 (1.8%)

HPV 1610 (1.9%)

2 (0.8%)8 (2.9%)4 (0.9%)0 (0.0%)4 (1.6%)

HPV 1820 (3.9%)5 (2.0%)15 (5.5%)5 (1.1%)0 (0.0%)5 (2.0%)

HPV 31

11 (2.1%)

1 (0.4%)10 (3.7%)

6 (1.3%)1 (0.5%)5 (2.0%)

HPV 3316 (3.1%)

3 (1.2%)13 (4.8%)

4 (0.9%)1 (0.5%)3 (1.2%)

HPV 3527 (5.2%)5 (2.0%)22 (8.1%)

14 (3.0%)

3 (1.4%)11 (4.4%)

HPV 397 (1.3%)2 (0.8%)5 (1.8%)2 (0.4%)0 (0.0%)2 (0.8%)

HPV 459 (1.7%)4 (1.6%)5 (1.8%)1 (0.2%)0 (0.0%)1 (0.4%)

HPV 519 (1.7%)1 (0.4%)8 (2.9%)3 (0.6%)0 (0.0%)3 (1.2%)

HPV 5237 (7.1%)

12 (4.8%)

25 (9.2%)

18 (3.8%)5 (2.2%)13 (5.2%)

HPV 569 (1.7%)4 (1.6%)5 (1.8%)1 (0.2%)0 (0.0%)1 (0.4%)

HPV 5810 (1.9%)

2 (0.8%)8 (2.9%)3 (0.6%)

1 (0.5%)2 (0.8%)

HPV 597 (1.3%)0 (0.0%)7 (2.5%)0 (0.0%)0 (0.0%)0 (0.0%)

The table shows the number (percentage) of participants who were high-risk HPV positive at baseline

Fig. 1 Genome-wide association results for prevalent high-risk HPV. λ = 1.02. a Manhattan plot (b) Quantile–quantile plot (c) Regional plot for rs149473200

Adebamowo et al. BMC Medical Genetics(2020) 21:231

Page 5 of 10

Table 2 Associations of the Top 20 SNPS with Prevalent Cervical high-risk Infections
SNP

Chr

Base Position

Near gene

Reference allele

MAF

OR

95% CI

P-valuers149473200

13

74,295,767

KLF12

G

0.03

7.06

3.19–15.63

1.43 × 10− 6

rs147344426

13

74,298,464

KLF12

G

0.03

7.06

3.19–15.63

1.43 × 10− 6

rs151071053

13

74,299,405

KLF12

T

0.03

7.06

3.19–15.63

1.43 × 10− 6

rs572823632

13

74,299,732

KLF12

GAA

0.03

7.06

3.19–15.63

1.43 × 10− 6

rs73010973

4

181,310,690

NCRNA00290

T

0.06

3.86

2.22–6.72

1.70 × 10− 6

rs73010975

4

181,310,704

NCRNA00290

T

0.06

3.86

2.22–6.72

1.70 × 10− 6

rs74739185

4

181,311,019

NCRNA00290

G

0.06

3.86

2.22–6.72

1.70 × 10− 6

rs79140020

4

181,311,020

NCRNA00290

T

0.06

3.86

2.22–6.72

1.70 × 10− 6

rs35833676

21

32,961,256

TIAM1

C

0.07

3.45

2.07–5.73

1.79 × 10− 6

rs3818252

20

58,675,675

C20orf197

C

0.57

2.22

1.60–3.10

2.06 × 10− 6

rs112893815

4

181,311,254

NCRNA00290

C

0.06

3.77

2.17–6.53

2.22 × 10− 6

a

a

–

8

74,725,256

UBE2W

G

–

3.31

2.01–5.44

2.42 × 10− 6

rs506594

11

64,162,897

RPS6KA4

T

0.77

0.44

0.31–0.62

2.67 × 10− 6

rs73010952

4

181,308,382

NCRNA00290

G

0.06

3.69

2.14–6.38

2.77 × 10− 6

rs111800742

4

181,308,587

NCRNA00290

C

0.06

3.69

2.14–6.38

2.77 × 10− 6

rs73010957

4

181,309,080

NCRNA00290

A

0.06

3.69

2.14–6.38

2.77 × 10− 6

rs6574170

14

74,729,207

VSX2

A

0.04

5.29

2.63–10.67

3.16 × 10− 6–

1736,374,963

LOC440434

TA

–

0.48

0.35–0.65

3.17 × 10− 6

rs17090215

13

74,039,057

KLF12

C

0.05

3.90

2.20–6.92

3.21 × 10−6

72,615,562

NEGR1

C

0.15

2.52

1.71–3.73

3.49 × 10− 6

rs375435036

1

a

a

For this analysis, 125 women with cervical hrHPV infections were compared to 392 women without cervical hrHPV infections at baseline. Base positions werebased on hg19; aThe variant is not in 1000 genomes v1, the nearest gene was obtained from variants surrounding the base location on the specific chromosome;
Odds Ratio (OR) and 95% Confidence Intervals (CI) were estimated using an additive genetic model; Models were adjusted for age, HIV status and the firstprincipal components of the genotypes

variant has not been included in the 1000 Genomes data
resources. However, we found that the variantssurrounding this region, Chr5:10847888–10,847,902, arelocated between Death Associated Protein gene (DAP)and Catenin Delta 2 (CTNND2) genes. Figure 2 shows a
Manhattan plot and a regional plot of association withpersistent cervical hrHPV infections. Other top variants
associated with persistent hrHPV infections werers200516199 upstream of MicroRNA 365b gene
(MIR365–2), OR: 7.71, p = 2.63 × 10− 7; variants clustered
upstream of Nuclear Receptor Subfamily 5 Group A
Member 2 gene (NR5A2) and Junctophilin Type 2 gene
(JPH2). Next, we conducted a replication study by identifying all SNPs associated with HPV and cervical neoplasia in other studies (Supplementary Table 1) andevaluated their association with hrHPV in the present
study, using an adjusted additive genetic model. We
found rs9893818 (OR: 0.88, p = 0.58 for prevalent
hrHPV; OR: 0.92, p = 0.82 for persistent hrHPV) andrs2299187 (OR: 0.95, p = 0.86 for prevalent hrHPV; OR:
1.13, p = 0.71 for persistent hrHPV) in our dataset but
they were not significantly associated with prevalent or
persistent cervical hrHPV infections (Supplemental
Table 2). Lastly, we conducted stratified analysis by HIV

status and found that none of the variants reached genomewide statistical significance (Supplemental Tables 3 and 4).

Discussion
This is the first GWAS of cervical hrHPV infection, to
our knowledge. The top three variants associated withprevalent cervical hrHPV infection were clustered in
KLF12, while those associated with persistent cervical
hrHPV infection were near DAP, CTNND2, MIR365–2
and NR5A2. These associations were borderline
genome-wide significant. It is well established that thedeterminants of prevalent and persistent cervical hrHPV
infections are different. Our finding of separate variants
associated with prevalent and persistent cervical hrHPV
suggests that their genetic risk factors may also differ.
The associated SNPs in KLF12, rs149473200 and
rs147344426, are eQTLs of CD3e molecule (CD3E), a protein coding gene which plays an essential role in T-cell development and its defects cause immunodeficiency. KLF12, a
protein coding gene, is overexpressed in human B and T
lymphocytes, CD8 T cells and natural killer cells [25]. Thesecells play important roles during immune response to
hrHPV infection, including recognizing and destroying
infected cells. hrHPV causes the immune system to becomeAdebamowo et al. BMC Medical Genetics(2020) 21:231

Page 6 of 10

Table 3 Associations of the Top 20 SNPS with Persistent Cervical high-risk Infections
SNP

Chr

Base Position

Near gene

Reference allele

MAF

OR

95% CI

P-value–

5

10,847,898

DAPa

C

–

6.87

3.41–13.84

7.15 × 10−8

rs143668247

1

199,701,882

NR5A2

C

0.35

3.66

2.24–5.97

2.03 × 10−7rs200516199

17

29,917,727

MIR365–2

TTTGA

0.04

7.71

3.54–16.78

2.63 × 10− 7

rs116834259

20

42,742,258

JPH2

T

0.11

4.42

2.50–7.81

3.15 × 10− 7

rs11452236

20

42,751,590

JPH2

C

0.13

4.03

2.34–6.92

4.78 × 10− 7

rs74358070

20

42,727,587

JPH2

T

0.11

4.24

2.41–7.47

5.52 × 10−7

rs16832308

2

133,253,243

GPR390

A

0.04

6.30

3.05–13.01

6.49 × 10−7

rs62167448

2

133,254,091

GPR39

C

0.04

6.30

3.05–13.01

6.49 × 10−7

rs150410476

11

37,223,676

C11orf74

A

0.03

8.31

3.60–19.16

6.80 × 10−7

rs12740341

1

199,699,781

NR5A2

C

0.26

3.18

2.01–5.03

7.94 × 10−7

rs79032354

20

42,732,460

JPH2

C

0.13

3.91

2.27–6.71

7.96 × 10−7

rs6130527

20

42,733,946

JPH2

G

0.13

3.91

2.27–6.71

7.96 × 10−7

rs4810411

20

42,751,472

JPH2

C

0.13

3.81

2.24–6.50

7.99 × 10−7rs2502139

1

199,695,633

NR5A2

A

0.27

3.17

2.00–5.02

8.94 × 10−7

rs34026413

1

199,695,074

NR5A2

A

0.27

3.10

1.97–4.88

7.94 × 10−6–

126,304,144

PAFAH2

C

–

10.19

4.01–25.92

7.94 × 10− 6

rs543084794

2

133,250,145

GPR39a

C

0.04

6.44

3.04–13.65

7.94 × 10− 6

rs79014529

20

42,717,781

TOX2

C

0.13

3.81

2.22–6.53

7.94 × 10− 6

rs1429702

1

199,694,059

NR5A2

T

0.27

3.10

1.96–4.87

7.94 × 10−6

rs6130520

20

42,716,399

TOX2

G

0.13

3.77

2.20–6.47

7.94 × 10−6a

For this analysis, 51 women with hrHPV infection at both the baseline and follow-up visits were compared to 355 women without hrHPV infections at either thebaseline or follow-up visits. Base positions were based on hg19; aThe variant is not in 1000 genomes v1, the nearest gene was obtained from variants surrounding
the base location on the specific chromosome; Odds Ratio (OR) and 95% Confidence Intervals (CI) were estimated using an additive genetic model; Models were
adjusted for age, HIV status and the first principal components of the genotypes

more tolerant to infection by avoiding cytolysis of host cells,
inhibiting interferon synthesis and cytotoxic T cell function,and inducing regulatory T cell infiltration [26–28]. This creates a cervical microenvironment that is susceptible to persistent infection and carcinogenesis. KLF12 has been linked
to several cancers [29–32], including head and neck cancers[33, 34], which are usually associated with hrHPV. A studyof HPV integration breakpoints in the human genome
showed that a copy of the virus was integrated between
KLF5 and KLF12 in HPV-positive SiHa cells [35]. Recently, awhole-genome sequencing study on HPV-positive
SiHa, HeLa and cervical carcinoma cells showed
KLF12 was one of the top three integration sites for
HPV [36]. Thus, KLF12 may play a major role in theunderlying mechanisms that lead to hrHPV infection,
persistence and cervical carcinogenesis.
A locus between CTNND2 and DAP in the short armof chromosome 5, had the strongest association withpersistent cervical hrHPV infections in the present study.
CTNND2 gene encodes an adhesive junction associatedprotein and is overexpressed in the cervix [25]. It has
been implicated in cancer formation and has been linked
to breast and ovarian cancers [37–39]. DAP encodes abasic, proline-rich protein which acts as a positive

mediator of programmed cell death that is induced byinterferon-gamma [40]. It negatively regulates autophagy
and is a substrate for mammalian target of rapamycin(mTOR) [41], which regulates different cellular processes. Results from GWASs show that DAP is associated with digestive disorders, gut microbiota, height andobesity [42–45]. There is some evidence that this geneplays a pro-apoptotic role in breast and cervical cancers[46–48]. Esteller et. al. showed that hypermethylation of
the CpG islands located in the promoter region of DAP
leads to transcriptional silencing thereby enabling malignant growth [49].
rs200516199 and rs143668247 near MIR365–2 andNR5A2 (LRH-1), respectively, were also associated withpersistent cervical hrHPV infections. Like CTNND2 and
DAP, MIR365–2 has also been linked to breast and cervicalcancers [50, 51]. It appears to have an oncogenic effect insome cancers [52, 53] and tumor suppressor effect in others[54–57]. Bioinformatics and experimental research studies
have proved that apoptotic markers BAX and BCL-2, are
two of the main targets of this microRNA [58, 59].
rs143668247 alters motifs in POU Class 5 Homeobox 1 (POU5F1) gene. Aberrant expression of thisgene in adult tissues is associated with tumorigenesis

Adebamowo et al. BMC Medical Genetics(2020) 21:231

Page 7 of 10

Fig. 2 Genome-wide association results for persistent high-risk HPV. λ = 1.00. a Manhattan plot (b) Quantile–quantile plot (c) Regional plot
for rs116834259[37]. rs143668247 is located 295 kb 5′ of NR5A2, anorphan receptor recently identified as a negative
modulator of hepatic inflammatory processes [60]. It
encodes a protein which is highly expressed in theliver and is involved in regulating the expression ofgenes for lipid metabolism, hepatitis B virus [61, 62]
and several cancers [63–69]. Although these genes
have not been previously linked to HPV infection,subsequent GWAS may confirm our findings.
Our study is limited by its exploratory nature. Given
the small sample size of this study the power of thestudy was limited. Thus, we may have missed associations with smaller effect sizes and we could not examine
the relationship between variants and type-specifichrHPV and by HIV status. Our replication study yielded
two SNPs, TMC6/TMC8:rs9893818 which was reported
to be associated with CIN3/cervical cancer [9] andCACNA2D1:rs2299187, which was associated withsurvival of head and neck squamous cell carcinoma in a
recent GWAS [70]. However, these variants were notassociated with hrHPV in our study. Also, rs7082598
variant in PRDX3 and rs2305809 variant in RPS19,

which were shown to be associated with HPV persistence in a candidate gene study conducted within Guanacaste cohort in Costa Rica, were not associated with
hrHPV in our study. This may be due to inadequate
sample size, variability in the types of hrHPV or population differences. Unlike our study population which wascomprised of only African women, the population of
Guanacaste is heavily admixed and has been described
as being composed mainly of European (42.5%) and Native American (38.3%) ancestries, with considerable African influence (15.2%) and a small influence from Asians(4%) [71]. The frequency of rs7082598 is 0.14 (AFR),
0.11 (AMR), 0.04 (ASN) and 0.08 (EUR) [72], our study
may have been underpowered to detect an association
with this variant. The frequency of rs2305809 is 0.89
(AFR), 0.52 (AMR), 0.56 (ASN) and 0.48 (EUR) [72],suggesting that most African women have this variant
regardless of their HPV status, which is most likely why
we were unable to detect an association between
rs2305809 and HPV in our study population. The findings from this exploratory study suggests that there are
significant associations between genetic variants andAdebamowo et al. BMC Medical Genetics(2020) 21:231

cervical hrHPV infection and larger studies are warranted. The strengths of our study include studying awell-characterized longitudinal cohort with multiple
hrHPV assessments in the participants. Secondly, themain loci identified have biological and functional support for a role in HPV infection and persistence. Lastly,
the variant frequencies we observed were similar between our samples and those of west African ancestry
samples in the 1000 Genomes dataset, validating the
genotype accuracy in our datasets.

Conclusion
In conclusion, our study yielded suggestive genetic risk
factors for prevalent and persistent cervical hrHPV
infections. Further investigations of genetic variation in
the KLF12, CTNND2 and DAP genes may provide
insight into mechanisms of susceptibility to hrHPV
infection and persistence. Larger discovery and replication studies are warranted to confirm these findings.

Page 8 of 10

Collaborative Center for Microbiome and Genomics Research Grant (NIH/
NHGRI 1U54HG006947). Sally Adebamowo is funded by the American Cancer
Society IRG-18-160-16.
The funders had no role in study design, data collection and analysis,
decision to publish, or preparation of the manuscripts.
Availability of data and materials
The datasets used and/or analyzed during the current study are available
from the corresponding author on reasonable request.
Ethics approval and consent to participate
The study was conducted according to the Nigerian National Code for
Health Research Ethics. Ethical approval to conduct this study was obtained
from the Institute of Human Virology Nigeria research ethics committee andUniversity of Maryland School of Medicine Institutional Review Board. Written
informed consent was obtained from all participants before enrollment in
the study.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
Department of Epidemiology and Public Health, University of Maryland
School of Medicine, 660 West Redwood Street, Howard Hall, Room 119,
Baltimore, MD 21201, USA. 2University of Maryland Greenebaum
Comprehensive Cancer Center, University of Maryland School of Medicine,
Baltimore, MD, USA. 3Center for Research on Genomics and Global Health,National Human Genome Research Institute, National Institutes of Health,Bethesda, MD, USA. 4Department of Obstetrics and Gynecology, National
Hospital Abuja, Abuja, Nigeria. 5Department of Obstetrics and Gynecology,
University of Abuja Teaching Hospital, Abuja, Nigeria. 6Institute of Human
Virology, University of Maryland School of Medicine, Baltimore, MD, USA.
7
Institute of Human Virology Nigeria, Abuja, Nigeria.
1

Supplementary Information
The online version contains supplementary material available at https://doi.
org/10.1186/s12881-020-01156-1.
Additional file 1: Supplemental Table S1.
Additional file 2: Supplemental Table S2. Replication of SNPs
Associated with Cervical high-risk Infections.
Additional file 3: Supplemental Table S3. Associations of the Top
SNPS with Cervical High-risk Infections in HIV-Negative Women.
Additional file 4: Supplemental Table S4. Associations of the Top
SNPS with Cervical High-risk Infections in HIV-Positive Women.
Additional file 5: Supplementary Figure S1. Principal components(PC) plot of the genotypes of the study participants.
Abbreviations
AGVP: African Genome Variation Project; BMI: Body mass index; CIN: Cervicalintraepithelial neoplasia; DEIA: DNA Enzyme Immunoassay; GWAS: Genomewide association studies; HPV: Human papillomavirus; hrHPV: High-risk
Human Papillomavirus; HWE: Hardy-Weinberg equilibrium; IQR: Interquartile
range; MAF: Minor allele frequency; MEGA: Multi-Ethnic Global Array;
OR: Odds ratio; PBWT: Positional Burrows-Wheeler transform; SNP: Single
nucleotide polymorphisms; UG2G: Uganda 2000 Genomes Project
Acknowledgments
We are very grateful to the women who participated in this study. We
acknowledge the past and present members of the H3Africa ACCME
Research Group, Research Associates and Volunteers who contributed to thisstudy, especially Dareng E, Famooto A, Obende K, Adebayo A, Ologun S,
Alabi B, Achara P, Bakare R, Dakum P. The content is solely the responsibilityof the authors and does not necessarily represent the official views of the
National Cancer Institute, or the National Institutes of Health.
Authors’ contributions
SA analyzed the data, interpreted the results and drafted the manuscript. AA
contributed to the data analysis. OO and RO provided clinical oversight forthe study. CA obtained funding for this study. AA, OO, RO, CR and CA
provided critical revisions to the manuscript. All the authors contributed tothe study implementation and approved the final version of the manuscript.
Funding
This work was supported by the UM-Capacity Development for Research in
AIDS Associated Malignancy Grant (NIH/NCI 1D43CA153792–01) and African

Received: 8 September 2019 Accepted: 25 October 2020

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